In general, the pathology of Alzheimer's Disease (AD) is not fully understood. Clinicians have a long-standing need to develop new therapy options based on pharmaceuticals and other treatments. Further, early detection of the onset of Alzheimer's disease is currently nearly impossible, but would be of great benefit for conducting clinical trials of new therapies.
To demonstrate the efficacy of a therapy in a clinical trial, it is necessary to recruit a population of patients that includes those who are most likely to benefit. Failure to do so greatly reduces the ability of a clinical trial to prove the efficacy of a treatment. This may lead to the rejection of medications or treatments that are effective, but whose effectiveness cannot be demonstrated through statistical means. The adequacy of the clinical trial population is an important factor in developing new therapies for Alzheimer's Disease.
Accurate diagnosis of various conditions of dementia is difficult in clinical practice today. Diagnosis is often attempted using neuropsychological tests (NPT). A wide range of NPTs are known, some borrowed from the intelligence quotient (IQ) domain and others devised specifically for dementias, e.g. ADAS-Cog. The determination of a diagnosis using NPT scores remains difficult or impossible in many circumstances.
Regarding Alzheimer's Disease, a designation known as “mild cognitive impairment” (MCI) has been adopted for clinical use. MCI is not yet an official diagnostic category, e.g. MCI does not have a DSM-IV code. MCI generally requires the presence of at least one impairment of cognitive function that does not seriously compromise a person's ability to function socially and professionally.
Only some of the patients diagnosed as being MCI will progress to Alzheimer's Disease. The conversion from MCI to AD may take up to several years. A means for determining which MCI patients will progress to AD would be of considerable use in the early detection of AD and in following the progress of its pathology.
In addition, clinicians are often faced with the challenge of comprehending the implications of a large number of clinical measurements. These may be performance tests, lab values, metrics derived from images, and the like. Further, there may be historical arrays of the same or similar information that need to be included as context from which important clinical decisions need to be made.
For example, in the evaluation of patients with cognitive complaints, clinicians often employ batteries of NPT tests. These tests attempt to quantify cognitive abilities in many dimensions, e.g. memory, executive control, and language. It is difficult for clinicians to use these arrays of information because of the clutter of data resulting from the large number of NPT tests, as well as the need to review scores across various cognitive dimensions and across time.
US Patent Publication 2006/0099624 discloses a method for providing personalized healthcare to a patient suspect of having or having AD which includes using information fusion or machine learning with heterogeneous data to provide a diagnosis, prognosis or treatment.
In general, these and other methods in the field can suffer from overfitting of the data which may cause incorrect diagnosis of a patient. Incorrect results include false positives and negatives, as well as poor sensitivity or specificity for identifying patients with mild cognitive impairment who are at risk, or in diagnosis.
There is a long-standing need for methods and systems to provide tools for physicians and clinicians which transform and present comparative patient conditions to provide a basis for interpretation, diagnosis and treatment options, as well as for detection of the onset of Alzheimer's disease.
There is a long-standing need for methods and systems to provide tools for physicians and clinicians for selecting a cohort group or a patient at risk of Alzheimer's disease from a population of patients with mild cognitive impairment.
There is a long-standing need for methods and systems to provide tools for physicians and clinicians to monitor the diagnosis, prognosis and course of treatment options in the progression of Alzheimer's disease.